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Found 2,795 Skills
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
End-to-end automated operation for publishing Zoom recordings as lectures on PORSEO LMS / AI PLAY GUILD, then automatically handing off to note membership article creation. It also supports a branch where Zoom recordings are not uploaded as lectures, but only converted into note articles with eye-catching images and screenshots. Responsible for searching unpublished Zoom recordings, matching with lecture candidates, retrieving VTT transcripts and chat logs, creating summaries/lecture data, generating YouTube-style thumbnails and applying Convex Storage, importing to Mux, publishing to production Convex, notifying Discord forums, handing off to note articles, and deleting incorrectly published videos. Used when requested with commands like "Turn this Zoom video into a lecture", "Find and publish unpublished videos", "Create and link lecture thumbnails", "Notify Discord about the video", "Create a note article after publishing", "Turn this Zoom recording into only a note article", "Don't upload it as a lecture", "Include note thumbnails and screenshots", "Delete this lecture video".
Academic literature orientation skill that searches papers via Consensus, builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a professionally formatted Word document (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — not a finished review, but an orientation guide that lets a researcher dive in confidently. Triggers: 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'. Do NOT trigger for single one-off paper searches where the user just wants a quick list — that's a plain Consensus search.
Draft concise morning meeting notes summarizing overnight developments, trade ideas, and key events for coverage stocks. Designed for the 7am morning meeting format — tight, opinionated, actionable. Triggers on "morning note", "morning meeting", "what happened overnight", "trade idea", "morning call prep", or "daily note".
Explicitly save an insight, decision, or learning to agentmemory's long-term storage. Use when the user says "remember this", "save this", or wants to preserve knowledge for future sessions.
Guide for implementing the Syncfusion ASP.NET Core Kanban component using Tag Helper syntax. Use this skill when building task boards, configuring columns and swimlanes, or enabling drag-and-drop. Covers card settings, dialogs, and binding remote data for ASP.NET Core MVC and Razor Pages.
Use this skill when integrating, configuring, or extending Modern Admin (`@modern-admin/*`) in a host project — i.e. wiring `ModernAdminModule.forRoot`, adding admin resources, configuring Better Auth/Prisma/Redis, declaring properties or `@Action`/`@Before`/`@After` hooks, setting up role permissions (`MaRole.permissions`), or troubleshooting auth/SPA 404s. Triggers on tasks that mention `@AdminResource`, `AdminController`, `adminSource`, `BetterAuthProvider`, `ModernAdminStaticUiModule`, `setupPrismaSystem`, `MaRole`, `rolesResourceId`, the `ma_*` schema fragment, or scaffolding `bun create @modern-admin`.
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
Day-one data bootstrapping for a new brain. Sequences the highest-leverage data sources to go from empty brain to useful brain in one session. Uses ClawVisor for safe credential handling — the agent never holds raw API keys. Covers Gmail import, calendar sync, contacts seeding, X/Twitter archive, conversation imports, and file archives. Use when a user has just finished gbrain setup and asks "now what?"
Audits AI-implemented work for honest completion. Runs independent-evaluator checks against task artifacts, transcripts, tests, CI evidence, requirement-to-test mapping, status front matter, and quality gates; flags skipped tests, weakened assertions, mock-only confidence, snapshot drift, happy-path-only coverage, flaky retries, and status/evidence mismatches. Use when validating completed Compozy tasks, AI-authored PRs, or codex-loop iterations. Do not use for real-user QA, persona/journey testing, exploratory charters, or product usability sessions; use qa-execution for those.
GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, KvikIO, cuCIM, cuxfilter, cuVS, cuSpatial, and RAFT. Use whenever the user mentions GPU/CUDA/NVIDIA acceleration, or wants to speed up NumPy, pandas, scikit-learn, scikit-image, NetworkX, GeoPandas, or Faiss workloads. Covers physics simulation, differentiable rendering, mesh ray casting, particle systems (DEM/SPH/fluids), vector/similarity search, GPUDirect Storage file IO, interactive dashboards, geospatial analysis, medical imaging, and sparse eigensolvers. Also use when you see CPU-bound Python code (loops, large arrays, ML pipelines, graph analytics, image processing) that would benefit from GPU acceleration, even if not explicitly requested.
Retrieves historical PubNub messages via Message Persistence (Storage & Playback). Covers timetoken-based pagination, per-channel ordering guarantees, offline catch-up flows, retention configuration, and the "catch-up tool not a data lake" principle. Use when fetching past messages, paginating with timetokens, building offline-resume UI, retrieving messages with actions, or configuring retention.